Purwanto Purwanto, Astuti Ike Sari, Rohman Fatchur, Utomo Kresno Sastro Bangun, Aldianto Yulius Eka
Department of Geography, Faculty of Social Sciences, Universitas Negeri Malang, No. 5 Semarang Road, Malang 65145, Indonesia.
Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Negeri Malang, No. 5 Semarang Road, Malang 65145, Indonesia.
Ecol Inform. 2022 Nov;71:101809. doi: 10.1016/j.ecoinf.2022.101809. Epub 2022 Sep 8.
The COVID-19 pandemic that has hit the whole world has caused losses in various aspects. Several countries have implemented lockdowns to curb the spread of the SARS-CoV-2 virus that caused death. However, for developing countries such as Indonesia, it is not suitable for lockdown because it considers the economic recession. Instead, the Large-scale Social Restrictions (LSSR) regulation is applied, the same as the partial lockdown. Thus, it is hypothesized that implementing LSSR that limits anthropogenic activities can reduce heat emissions and air pollution. Utilization of remote sensing data such as Terra-MODIS LST and Sentinel-5P images to investigate short-term trends (i.e., comparison between baseline year and COVID-19 year) in surface temperature, Surface Urban Heat Islands Intensity (SUHII), and air pollution such as NO, CO, and O in Malang City and Surabaya City, East Java Province. Spatial downscaling of LST using the Random Forest Regression technique was also carried out to transform the spatial resolution of the Terra-MODIS LST image to make it feasible on a city scale. Raster re-gridding was also implemented to refine the Sentinel-5P spatial resolution. The accuracy of LST spatial downscaling results is quite satisfactory in both cities. Surface temperatures in both cities slightly decreased (below 1 °C) during LSSR was applied ( < 0.05). SUHII in both cities experienced a slight increase in both cities during LSSR. NO gas was reduced significantly ( < 0.05) in Malang City (∼38%) and Surabaya City (∼28%) during LSSR phase due to reduced vehicle traffic and restrictions on anthropogenic activities. However, CO and O gases did not indicate anomaly during LSSR. Moreover, this study provides insight into the correlation between SUHII change and the distribution of air pollution in both cities during the pandemic year. Air temperature and wind speed are also added as meteorological factors to examine their effect on air pollution. The proposed models of spatial downscaling LST and re-gridding satellite-based air pollution can help decision-makers control local air quality in the long and short term in the future. In addition, this model can also be applied to other ecological research, especially the input variables for ecological spatial modeling.
席卷全球的新冠疫情已在各方面造成损失。多个国家实施封锁措施以遏制导致死亡的严重急性呼吸综合征冠状病毒2（SARS-CoV-2）病毒的传播。然而，对于印度尼西亚这样的发展中国家而言，考虑到经济衰退，实施封锁并不合适。相反，该国实施了大规模社会限制（LSSR）规定，这与部分封锁类似。因此，有假设认为，实施限制人为活动的LSSR能够减少热量排放和空气污染。利用诸如Terra-MODIS陆地表面温度（LST）和哨兵-5P图像等遥感数据，来调查东爪哇省玛琅市和泗水市地表温度、城市热岛强度（SUHII）以及诸如一氧化氮（NO）、一氧化碳（CO）和臭氧（O）等空气污染的短期趋势（即基准年份与新冠疫情年份之间的比较）。还利用随机森林回归技术对LST进行空间降尺度处理，以转换Terra-MODIS LST图像的空间分辨率，使其在城市尺度上可行。还实施了栅格重采样以细化哨兵-5P的空间分辨率。在这两个城市中，LST空间降尺度结果的精度都相当令人满意。在实施LSSR期间，两个城市的地表温度均略有下降（低于1摄氏度）（P<0.05）。在实施LSSR期间，两个城市的SUHII均略有上升。在LSSR阶段，由于车辆交通减少和人为活动受限，玛琅市（约38%）和泗水市（约28%）的NO气体显著减少（P<0.05）。然而，CO和O气体在LSSR期间未显示异常。此外，本研究深入探讨了疫情年份这两个城市中SUHII变化与空气污染分布之间的相关性。还将气温和风速作为气象因素纳入，以研究它们对空气污染的影响。所提出的LST空间降尺度模型和基于卫星的空气污染重采样模型，可帮助决策者在未来长期和短期内控制当地空气质量。此外，该模型还可应用于其他生态研究，尤其是生态空间建模的输入变量。
